The purpose of this study is to develop a matrix for selecting methods for forecasting the socio-economic development of regions. The scientific novelty of the research lies in the classification of existing approaches used to address this issue, the identification of their advantages and limitations, the specification of required data and resources, the consideration of uncertainty factors and forecast-specific tasks, and the determination of the planning horizon. The study employs such methods like a systems approach, as well as comparative and retrospective analyses. The findings, obtained through a review of publications on regional socio-economic development forecasting over the past twenty years, may be useful both to the academic community and to decision-makers involved in related policy and management processes.

The purpose of this study is to analyse current challenges in the development of domestic agriculture and to identify key methods for addressing them effectively within the framework of public administration. The author proposes a modification of the program-target approach, involving its division into two analytical domains: factors that promote sectoral development and those that constrain growth, followed by their further specification as individual target factors. These target factors were subjected to situational analysis in order to determine the most appropriate intervention mechanisms for modernising the agricultural sector. The study identifies five principal factors shaping sectoral development. For each of these, a set of policy measures aimed at progressive growth is proposed, including financial support for agriculture, export promotion, land reclamation infrastructure development, production intensification, continuation and expansion of import substitution programmes, and rural territorial development as an indirect mechanism of agricultural support. The empirical basis of the research consists of statistical data from Rosstat related to sectoral performance, innovation dynamics in the economy, and indicators of rural territorial development. The concluding part of the article presents an assessment of development factors within the Russian agricultural sector and evaluates the current operating conditions of agricultural production. The findings and conclusions of the study are expected to be of interest to specialists engaged in the governance and strategic development of the agroindustrial complex.

The article presents a comprehensive analysis of the transformation of the non-profit sector (NPS) across the regions of the Russian Federation based on the Region–NPO ranking (2020–2025). The aim of the study is to identify, through this analytical instrument, key changes in the development of socially oriented non-profit organizations (SONPOs), major trends in the formation of the third sector, and the factors influencing these processes. Drawing on eight ranking criteria and 54 indicators, the paper examines structural transformations within the non-profit sector, the evolving interaction between SONPOs and key stakeholders, changes in support mechanisms, and the specific features of regional third-sector ecosystems. Particular attention is paid to the reduction of interregional disparities and the formation of sustainable development models. The study explores the principal trends in the development of sectoral infrastructure, financial sustainability, and citizen engagement in non-profit activities, as well as the dynamics in the number of organizations. The findings make it possible to identify promising directions for governmental and civic support, as well as to determine success factors and regional typologies of development.

The digital transformation of resource-supplying organizations in Russia is becoming a key element in ensuring the sustainable development of the public utilities sector. In the context of increasing demand for energy efficiency, automation, and transparency of business processes, companies are progressively implementing advanced technologies ranging from smart metering systems and remote monitoring to big data analytics and artificial intelligence. These solutions enable organizations to optimize operating costs, reduce resource losses, improve forecasting accuracy, and enhance the quality of customer service. The objective of this study is to develop a process-based model of digital transformation for a resource-supplying organization. The relevance of the research is determined, on the one hand, by the need to ensure both the sustainable development of public utility enterprises and the accessibility of their services to the population, and, on the other hand, by the necessity to align with national regulatory priorities and state policy. In particular, this includes achieving the objectives of the national project “Digital Economy” and the ministerial project “Smart City” implemented by the Ministry of Construction of the Russian Federation. The article presents an analysis of the impact of methodological and practical approaches to the implementation of innovative technologies, modern services, and digital platforms on managerial decision-making processes. The study employs such research methods as comparative and logical analysis, including a review of academic literature. The findings may be of practical relevance to resource-supplying organizations and to the academic community in the development of effective approaches to managing public utility infrastructure.

In the contemporary labour market, demand for human resource management (HRM) specialists is steadily increasing. However, a comprehensive conceptual framework for this professional field still requires further development due to the fragmented coexistence of various research approaches, including economic, personnel-administrative, and socio-psychological perspectives. In the course of the study, the authors relied on an integrative, multi-aspect methodology of human resource management developed by them. The purpose of the research is to analyse the extent to which the actual qualification level of HRM specialists, as well as undergraduate and graduate students enrolled in programmes such as “Human Resource Management” and “Personnel Management in Organisations,” corresponds to state and industry standards. The research methods included semi-structured interviews with HR department staff and line managers of enterprises in Naberezhnye Chelny, as well as a questionnaire survey of university students in the Republic of Tatarstan based on a multistage combined sampling design. Thus, the empirical base of the study comprised HR professionals, line managers, and university students. The findings reveal a significant gap between experts’ perceptions of the professional competencies required of HRM specialists and the actual level of competency development among HR department employees. It was also established that students majoring in management disciplines do not possess a sufficiently formed understanding of the content and scope of their future professional activities. The multi-focus framework of the concept of “personnel” and the multi-aspect approach to the functional content of human resource management proposed by the authors may be applied both to improve the performance of corporate HR departments and to enhance the training of future HR professionals.

Dynamism is an ability to qualitatively change, influencing the socioeconomic situation, and is an important characteristic of human resources (HR) as a scientific category. The purpose of the paper is to identify trends and characteristics of management discourse related to HR dynamism and developing in the information economy. This research identifies stages in researching HR as a dynamic category and identifies an impact of the ICT on studying relationships between HR, management practices, and economic systems’ performance. It also identifies ways for HR-practices development and touches on the issue of synergy between HR and technology. The primary research method is substantive and conceptual analysis of scientific works from recent decades. The results of the paper may be useful to scholars and practitioners working on human resources management.

The lack of consensus regarding quantitative measures for assessing text originality gives rise to the problem of interpreting the results generated by algorithms of information systems designed to detect academic borrowing in texts, as well as the comparability of expert evaluations of the originality of intellectual outputs. The aim of this study is to reveal the nature and essence of the phenomenon of academic borrowing through the methodology of knowledge management. The author considers quality management of the work performed by research units as a new function of knowledge management capable of regulating the quality of scientific knowledge. An original interpretation of the nature and essence of academic borrowing is proposed, distinguishing between its epistemological nature and its ethical-deontological essence. It is demonstrated that the contemporary (1990–2025) discourse on academic borrowing has been shaped by digital transformation and comprises approximately sixty definitions, which the author classifies into three groups. This inventory is conducted with a view to constructing a systematic terminological framework for academic borrowing. The findings of the study may be useful to specialists in general issues of the science of science and epistemology; in management studies, particularly in the field of knowledge management, including the organization and supervision of research activities; in the regulation of copyright and intellectual property rights; in the preparation, editing, and processing of academic texts; and to faculty members, students, and postgraduate researchers engaged in these areas, as well as to all those who require skills in academic writing.

State policy in the field of science and higher education is aimed at the modernization of educational institutions in order to ensure their closer alignment with labor market demands and societal needs. The purpose of this study is to assess the current parameters and operating conditions of educational institutions, taking into account the specific characteristics of the agro-industrial complex. The article provides an overview of the agricultural higher education system and presents an analysis of the current state of the network of educational organizations. Particular attention is paid to their structural features, elements, interconnections, and operational efficiency. The object of the study is the network of higher education institutions that train specialists for the agro-industrial complex, while the subject of the study is the efficiency of these educational institutions, as well as the factors, relationships, models, and algorithms governing the interaction of elements within their organizational systems. The data sources used in the study include strategic, methodological, organizational, and other materials characterizing the activities of educational institutions subordinate to the Ministry of Agriculture of the Russian Federation and the Ministry of Science and Higher Education of the Russian Federation, as well as analytical and statistical information. The findings of the study may be used by government authorities (primarily the Ministry of Agriculture of the Russian Federation) in managing the activities of agricultural educational institutions in order to obtain a more comprehensive assessment of the performance of subordinate organizations. In addition, the results can be applied in the development of prospective (strategic) plans for the advancement of specialized universities under contemporary conditions.

The purpose of the study is to systematize project experience management (PEM) tools and to develop recommendations for Russian industrial enterprises. The methodology employed in the research is based on an analysis of publications by Russian and international scholars, the examination of selected project management case studies, and expert assessments provided by experienced employees of industrial companies directly involved in project activities. The findings of the study are as follows. First, the main stages of project experience management are identified. Second, a classification of project experience management mechanisms is proposed, taking into account the management of both formalized and tacit knowledge, and practical tools and IT solutions are systematized. Third, key development trends in project experience management are determined. Fourth, a lag in the maturity level, technological support, and implementation of a knowledge-oriented organizational culture within Russian enterprises’ project experience management practices is revealed. The practical significance of the research lies in the development of recommendations for Russian manufacturing companies aimed at overcoming barriers to the implementation of advanced and best-practice PEM tools.

At the current stage of digital transformation, the strategic role of marketing in the management of trading companies is significantly increasing. The integration of artificial intelligence (AI)-based technologies — such as AI agents, synthetic respondents, AI-powered CRM systems, and predictive analytics — is transforming not only the functions but also the very nature of marketing management. In conditions of a highly turbulent external environment and sanctions-related constraints, the use of AI-based tools enables companies to develop flexible and adaptive strategies, make decisions in real time, and build personalized customer interactions. The aim of this study is to analyze the transformation of marketing management under the influence of AI technologies and to identify their contribution to the resilience of trading companies. The article examines the theoretical aspects of marketing management, the classification of its tools, as well as the risks and barriers associated with the application of artificial intelligence. The result of the research is the development of an authorial model for integrating AI-based marketing into the strategic management system of a trading company, as well as a classification of tools taking into account their strategic role and practical applications. The findings of the study may be useful for managers of trading companies, specialists in strategic development and digital transformation, as well as researchers in the field of management seeking to enhance business resilience and adaptability in conditions of external turbulence.

This study examines the impact of disinformation, specifically Plandemic, on public health responses within the context of COVID-19. The IDOM-H Framework integrates information economics, decision-making, and platform governance to examine how disinformation online affects epidemiological trends in the United States, Canada, Australia, New Zealand, and Ireland. A mixed-methods approach integrates official COVID-19 data with Facebook engagement and Google Trends. findings show a moderate and positive relationship (r = 0.62–0.63) between exposure to disinformation and total COVID-19 cases and deaths. While post-publication audience metrics increased, there was no significant association (p = 0.8021) between social media engagement and new daily cases. Subsequent research should utilize Granger causality and instrumental variable models to circumvent correlation limitations. Disinformation has no impact on case results but undermines public trust and causes long-term behavior modification. Targeted digital literacy and open platform governance are necessary to reduce long-term harm.

Corporate bankruptcy can be understood as a phase-based managerial process in which weak signals, together with the informational noise that obscures them, shape the trajectory of organizational degradation long before the actual collapse occurs. This conclusion emerges from shifting the focus of bankruptcy diagnostics away from traditional accounting and financial reporting toward institutional sensitivity. The concept of the phase dynamics of bankruptcy is synthesized from the phenomenology of the discrepancy between declared and actual practices, the assessment of feedback intensity, and the tonal analysis of a company’s public communications. The aim of this study is to develop a phase model for the early diagnosis of bankruptcy and to determine the threshold of loss of reflexivity, which marks a point of no return for the managerial system. The empirical part of the study includes the reconstruction of pre-crisis bankruptcy profiles of Enron, Long-Term Capital Management, and Barings Bank. Based on qualitative and quantitative analysis of behavioral patterns and public communications using the authors’ original indicators, it was established that a stable simultaneous exceedance of their threshold values is accompanied by the contraction of the “window of opportunity” for decisionmakers and by an acceleration of escalation dynamics. The findings allow a shift in emphasis from reactive to proactive management, thereby reducing the likelihood of an avalanche-like transition to the irreversible phase of crisis.

The article provides an overview of academic events and professional discussions held within the framework of the annual international scientific and practical conference “Asset Management”, which took place in December 2025 at MGIMO University (Russia). The relevance of the conference topic — “Artificial intelligence in economic decision–making: assets, actors, strategies” — is due to the modern exponential growth in the introduction of artificial intelligence (AI) technologies in all areas of the economy, corporate governance and public administration, and human life, which is confirmed by the results of reports and forecasts by international consulting companies, as well as the conclusions of russian experts. In this regard, the purpose of the conference, which brought together more than 350 participants from our country — students of classical, economic, technical, and law universities in Moscow, St. Petersburg, Tula, Saratov, Novosibirsk, Ufa, and other russian cities.; employees of scientific institutes, state corporations and private companies, as well as foreign researchers from the Czech Republic, China, Kazakhstan, Uzbekistan, Kyrgyzstan, and Azerbaijan, representing different generations and professions, have formed an active scientific platform for exchanging opinions and developing new knowledge on current trends, advantages, risks, and limitations associated with AI. Within the framework of the plenary session, practical professional discussion and six sections of the conference, the results of research carried out using methods of economic and mathematical modeling, systematic, critical historical and causal analysis, scenario approach and forecasting were presented. The participants’ reports reviewed the results of modeling economic and managerial decisions obtained using sovereign AI models both during the implementation of national economic development strategies by the state actor, and in the process of a comprehensive assessment of the sensitivity of various sectors of the economy to the introduction of AI, identifying key prospects for the formation of companies competitive advantages in the face of a sharp increase in the introduction of AI technologies and new requirements towards professional competencies in the labor market. Special attention at the conference was paid to updating the AI legal regulation.